a. Field of the Invention
This invention relates to a knowledge data base processing system having functions for updating the indices of certainty (certainty factors), which are applied to individual event propagation routes or the like, and for generating inferential information in an inference expert system adapted to perform inference of causes of events or inference of secondary effects of the events.
b. Description of the Related Art
Improvements and maintenance by a knowledge engineer are indispensable for actual updating of a knowledge data base because the preparation of a knowledge data base is based principally on human experiences and inference. Several proposals have hence been made from the viewpoints of optimization and/or automation of the updating of such a knowledge data base.
Unexamined Japanese Patent Publication (KOKAI) No. 60-24647 proposes a method for allocating intra-system resources in a system, to be shared by plural software units, in the form of application and evaluation of a knowledge base and, further, for creation of codes and selection of any recessive codes on the basis of the evaluation. In addition, according to the learning control method disclosed in Unexamined Japanese Patent Publication (KOKAI) No. 60-8902, a response obtained when an object to be controlled has been controlled by control information called beforehand from a file is evaluated and the rule is then written in the file in accordance with an index of the evaluation. The above proposals both involve the procedures whereby a response from a series of operations for an applied object is evaluated and a code or rule obtained by the evaluation is added to or deleted from a data base.
In the inference of an event, mere addition or deletion of rules based on the evaluation of an actual experience; on the object provides the knowledge data base with no sufficient ground or flexibility as long as the index of certainty (certainty factor) is fixed. It is also difficult to say that there is established a method for applying the evaluation results of actual experience to certainty factors.
As a known example of certainty factor, Unexamined Japanese Patent Publication (KOKAI) No. 1-265311 discloses a method for determining more practical certainty by providing the intensity of a process quantity, specifically the derivative with respect to time, with values of certain factors from 0 to 1. According to the method, the functional relation itself of the certainty factor can be modified depending on the cause. The cause is the intensity (the rate of a change) of the above process quantity so that automatic updating of the certainty factor is not performed based on an event actually experienced. In other words, an operator or knowledge engineer of a plant allocates the functional relation itself of certainty factor to each process quantity, which is to be controlled, manually on the basis of the past experiences. This method is therefore different in nature from the method such that, as in the present invention, the history of a real event is positively evaluated and is input to automatically update the certainty factor higher.
Further, Unexamined Japanese Patent Publication (KOKAI) No. 1-22933 discloses an inference system in which a conclusion inferred by an inference engine is judged to be correct or not by a user and the certainty factor of a rule in a knowledge base can be corrected by inputting information on the correctness or incorrectness of the conclusion. The certainty factor itself can also be corrected in this known example, but the correction is governed by the user's judgment.
As has been described above, the conventional techniques involve problems to the extent that they are insufficient in the reflection of characteristics of an object of application, objectivity as an index of certainty (certainty factor) is given based on experiences, both time and labor are required for user's judgment as cause candidate items for inferred results are provided unlimitedly, and the maintenance of certainty factors in a knowledge data base requires both judgment and labor on the side of a knowledge engineer.